PurposeThe purpose of this paper based on compensation theory, is to incorporate perceived technical security protection into the theory of planned behavior and examined factors affecting end‐user security behaviors, specifically, compliance with security policies.Design/methodology/approachAn online survey is conducted to validate the proposed research model. The survey is sent out to an industrial panel. A total of 176 usable responses are received and used in the data analysis.FindingsThe results show that both perceived behavioral control (PBC) and attitude have significant impact on intention to comply with security policy. Perceived technical protection affects behavioral intentions both indirectly, through PBC, and directly. The negative direct effect (i.e. perceived high technical protection leads to low intention to comply with security policy) suggests possible risk compensation effects in the information security context.Practical implicationsThis result should be of interest to practitioners. In practice (e.g. during security training), the power and capability of technical protection mechanisms should not be exaggerated. Instead, its limitations and drawbacks should be emphasized, so that end‐users will adopt more cautious security practices and adhere to the requirements of the organization's security policies.Originality/valueThis paper embeds risk compensation theory within the security policy compliance context and offers a useful starting point for further empirical examination of this theory in information security context.

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The dynamics of an extended, spatiotemporally chaotic system might appear extremely complex. Nevertheless, the local dynamics, observed through a finite spatiotemporal window, can often be thought of as a visitation sequence of a finite repertoire of finite patterns. To make statistical predictions about the system, one needs to know how often a given pattern occurs. Here we address this fundamental question within a spatiotemporal cat, a one-dimensional spatial lattice of coupled cat maps evolving in time. In spatiotemporal cat, any spatiotemporal state is labeled by a unique two-dimensional lattice of symbols from a finite alphabet, with the lattice states and their symbolic representation related linearly (hence ‘linear encoding’). We show that the state of the system over a finite spatiotemporal domain can be described with exponentially increasing precision by a finite pattern of symbols, and we provide a systematic, lattice Green’s function methodology to calculate the frequency (i.e., the measure) of such states.

Abstract:We consider the problem of orchestrating the execution of workflow applications structured as Directed Acyclic Graphs (DAGs) on parallel computing platforms that are subject to fail-stop failures. The objective is to minimize expected overall execution time, or makespan. A solution to this problem consists of a schedule of the workflow tasks on the available processors and of a decision of which application data to checkpoint to stable storage, so as to mitigate the impact of processor failures. For general DAGs this problem is hopelessly intractable. In fact, given a solution, computing its expected makespan is still a difficult problem. To address this challenge, we consider a restricted class of graphs, Minimal Series-Parallel Graphs (M-SPGs). It turns out that many real-world workflow applications are naturally structured as M-SPGs. For this class of graphs, we propose a recursive list-scheduling algorithm that exploits the M-SPG structure to assign sub-graphs to individual processors, and uses dynamic programming to decide which tasks in these sub-gaphs should be checkpointed. Furthermore, it is possible to efficiently compute the expected makespan for the solution produced by this algorithm, using a first-order approximation of task weights and existing evaluation algorithms for 2-state probabilistic DAGs. We assess the performance of our algorithm for production workflow configurations, comparing it to (i) an approach in which all application data is checkpointed, which corresponds to the standard way in which most production workflows are executed today; and (ii) an approach in which no application data is checkpointed. Our results demonstrate that our algorithm strikes a good compromise between these two approaches, leading to lower checkpointing overhead than the former and to better resilience to failure than the latter. To the best of our knowledge, this is the first scheduling/checkpointing algorithm for workflow applications with fail-stop failures that considers workflow structures more general than mere linear chains of tasks.Key-words: workflow, checkpoint, fail-stop error, resilience. Stratégies de checkpoint pour les workflows en présence d'erreurs fatalesRésumé : Ce rapport considère l'ordonnancement de workflows (applications structurées en forme de graphes de tâches acycliques, ou DAGs) sur des plates-formes parallèlesà grandé echelle, soumisesà des erreurs fatales. L'objectif est de minimiser l'espérance du temps total d'exécution, ou makespan. Une solutionà ce problème comprend l'allocation ordonnée des tâches aux processeurs, et les décisions de checkpoint: quelles tâches sont suivies d'un checkpoint? Même pour une solution donnée, le calcul du makespan reste difficile. Nous nous restreignonsà une classe de DAGs particuliers, les graphes séries-parallèles minimaux, ou MSPGs. De nombreux workflows issus des applications ont pour graphe un M-SPG. Pour de tels graphes, nous proposons un algorithme qui utilise la structure récursive du M-SPG pour allouer des sous-graphesà chaque pro...

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The RAN architecture towards mobile 5G and beyond is undergoing a fundamental evolution, which brings optics into the radio world. Fronthaul is a new segment that leverages on the advantages of optical communication for RAN transport. However, the current fronthaul architecture shows a fixed connection between an RRH and a BBU, which leads to inefficient resource utilization. In this paper, we focus on the fronthaul flexibility that allows "any-RRH to any-BBU" connection. In particular, we consider a CoMP service and discuss how flexible optical fronthaul helps to improve its performance. To achieve this goal, we propose an SDN-enabled orchestration for coordinating radio and optical access networks. Under this unified control manner, the agile RRH-BBU mapping can be reached through lightpath reconfiguration. To further verify the benefits of flexibility, we experiment the CoMP service in the cloud radio over flexible optical fronthaul (CRoFlex) testbed. Experimental results demonstrate the proposed SDN-enabled flexible optical fronthaul can improve the CoMP performance by optimizing the RRH-BBU mapping.

Applications supporting various multimedia data in wireless multimedia sensor networks (WMSNs) have specific QoS requirements on bandwidth, delay, and/or packet loss. Perception of applications' QoS requirements and detection of link states are indispensable for the design of QoS-aware routing mechanism. Software defined networking (SDN) is suitable for the purpose since it provides visibility of network resources and programmable interfaces. OpenFlow is the most recognized realization of SDN. We propose a QoS-aware routing mechanism for OpenFlow-enabled WMSNs. The mechanism consists of a framework and routing algorithms on SDN controller. The framework includes two functions: detection of link states among OpenFlow-enabled nodes and determination of flow's QoS requirements. The routing algorithms are achieved in two steps. First, the SDN controller seeks the feasible paths that satisfy QoS requirements of a flow. If there is no path which satisfies the required QoS, the path will be decided by the proposed algorithms depending on flow types: delay-sensitive, bandwidth-sensitive, and best-effort traffic. We conducted experiments on a SDN testbed to evaluate our mechanism and compared the results with conventional routing protocols. The results show that proposed routing mechanism increases the throughput by 43% for video data and reduces the delay by more than 30% for audio data.